scholarly journals Fine-mapping cis-regulatory variants in diverse human populations

2018 ◽  
Author(s):  
Ashley K. Tehranchi ◽  
Brian Hie ◽  
Michael Dacre ◽  
Irene M. Kaplow ◽  
Kade P Pettie ◽  
...  
Keyword(s):  
Long Range ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Chromatin Accessibility ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Diverse Populations ◽  
Regulatory Variants ◽  
Causal Variants ◽  
In Cis

AbstractGenome-wide association studies (GWAS) are a powerful approach for connecting genotype to phenotype. Most GWAS hits are located in cis-regulatory regions, but the underlying causal variants and their molecular mechanisms remain unknown. To better understand human cis-regulatory variation, we mapped quantitative trait loci for chromatin accessibility (caQTLs)—a key step in cis-regulation—in 1000 individuals from 10 diverse populations. Most caQTLs were shared across populations, allowing us to leverage the genetic diversity to fine-map candidate causal regulatory variants, several thousand of which have been previously implicated in GWAS. In addition, many caQTLs that affect the expression of distal genes also alter the landscape of long-range chromosomal interactions, suggesting a mechanism for long-range expression QTLs. In sum, our results show that molecular QTL mapping integrated across diverse populations provides a high-resolution view of how worldwide human genetic variation affects chromatin accessibility, gene expression, and phenotype.

scholarly journals Fine-mapping cis-regulatory variants in diverse human populations

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Ashley Tehranchi ◽  
Brian Hie ◽  
Michael Dacre ◽  
Irene Kaplow ◽  
Kade Pettie ◽  
...  
Keyword(s):  
Long Range ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Chromatin Accessibility ◽  
Editorial Note ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Diverse Populations ◽  
Regulatory Variants ◽  
In Cis

Genome-wide association studies (GWAS) are a powerful approach for connecting genotype to phenotype. Most GWAS hits are located in cis-regulatory regions, but the underlying causal variants and their molecular mechanisms remain unknown. To better understand human cis-regulatory variation, we mapped quantitative trait loci for chromatin accessibility (caQTLs)—a key step in cis-regulation—in 1000 individuals from 10 diverse populations. Most caQTLs were shared across populations, allowing us to leverage the genetic diversity to fine-map candidate causal regulatory variants, several thousand of which have been previously implicated in GWAS. In addition, many caQTLs that affect the expression of distal genes also alter the landscape of long-range chromosomal interactions, suggesting a mechanism for long-range expression QTLs. In sum, our results show that molecular QTL mapping integrated across diverse populations provides a high-resolution view of how worldwide human genetic variation affects chromatin accessibility, gene expression, and phenotype.Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that minor issues remain unresolved (<xref ref-type="decision-letter" rid="SA1">see decision letter</xref>).

scholarly journals Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Matthias Thurner ◽  
Martijn van de Bunt ◽  
Jason M Torres ◽  
Anubha Mahajan ◽  
Vibe Nylander ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Pancreatic Islet ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Human Islets ◽  
Chromatin Accessibility ◽  
Chromatin State ◽  
Open Chromatin ◽  
Genome Wide Association Studies

Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

scholarly journals Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

2017 ◽  
Author(s):  
Matthias Thurner ◽  
Martijn van de Bunt ◽  
Jason M Torres ◽  
Anubha Mahajan ◽  
Vibe Nylander ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Pancreatic Islet ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Human Islets ◽  
Chromatin Accessibility ◽  
Chromatin State ◽  
Open Chromatin ◽  
Genome Wide Association Studies

AbstractHuman genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n=17) and DNA methylation (whole-genome bisulphite sequencing, n=10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

scholarly journals Trans-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

2020 ◽  
Author(s):  
Anubha Mahajan ◽  
Cassandra N Spracklen ◽  
Weihua Zhang ◽  
Maggie CY Ng ◽  
Lauren E Petty ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Fine Mapping ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Population Diversity ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Diverse Populations ◽  
Genome Wide

We assembled an ancestrally diverse collection of genome-wide association studies of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent). We identified 277 loci at genome-wide significance (p<5x10-8), including 237 attaining a more stringent trans-ancestry threshold (p<5x10-9), which were delineated to 338 distinct association signals. Trans-ancestry meta-regression offered substantial enhancements to fine-mapping, with 58.6% of associations more precisely localised due to population diversity, and 54.4% of signals resolved to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying foundations for functional investigations. Trans-ancestry genetic risk scores enhanced transferability across diverse populations, providing a step towards more effective clinical translation to improve global health.

scholarly journals Tissue-specific multiOMICs analysis of atrial fibrillation

2020 ◽  
Author(s):  
Ines Assum ◽  
Julia Krause ◽  
Markus O. Scheinhardt ◽  
Christian Müller ◽  
Elke Hammer ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Molecular Networks ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Tissue Specific ◽  
Protein Levels ◽  
Atrial Tissue ◽  
Regulatory Variants

AbstractGenome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, novel multiOMICs approaches are needed for deciphering the underlying molecular networks. Here, we integrated genomics, transcriptomics, and proteomics of human atrial tissue which allowed for identifying widespread effects of genetic variants on both transcript (cis eQTL) and protein (cis pQTL) abundance. We further established a novel targeted trans QTL approach based on polygenic risk scores to identify candidates for AF core genes. Using this approach, we identified two trans eQTLs and four trans pQTLs for AF GWAS hits, and elucidated the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multiOMICs method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization.

scholarly journals A method for scoring the cell type-specific impacts of noncoding variants in personal genomes

2020 ◽  
Vol 117 (35) ◽  
pp. 21364-21372
Author(s):  
Wenran Li ◽  
Zhana Duren ◽  
Rui Jiang ◽  
Wing Hung Wong
Keyword(s):  
Human Genetics ◽  
Association Studies ◽  
Region Of Interest ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Genomic Region ◽  
Personal Genome ◽  
Genome Wide Association Studies ◽  
Causal Variants ◽  
Context Specific

A person’s genome typically contains millions of variants which represent the differences between this personal genome and the reference human genome. The interpretation of these variants, i.e., the assessment of their potential impact on a person’s phenotype, is currently of great interest in human genetics and medicine. We have developed a prioritization tool called OpenCausal which takes as inputs 1) a personal genome and 2) a reference context-specific TF expression profile and returns a list of noncoding variants prioritized according to their impact on chromatin accessibility for any given genomic region of interest. We applied OpenCausal to 6,430 samples across 18 tissues derived from the GTEx project and found that the variants prioritized by OpenCausal are highly enriched for eQTLs and caQTLs. We further propose a strategy to integrate the predicted open scores with genome-wide association studies (GWAS) data to prioritize putative causal variants and regulatory elements for a given risk locus (i.e., fine-mapping analysis). As an initial example, we applied this method to a GWAS dataset of human height and found that the prioritized putative variants and elements are correlated with the phenotype (i.e., heights of individuals) better than others.

scholarly journals Functional Interrogation of Enhancer Connectome Prioritizes Candidate Target Genes at Ovarian Cancer Susceptibility Loci

2021 ◽  
Vol 12 ◽  
Author(s):  
Wei Wang ◽  
Fengju Song ◽  
Xiangling Feng ◽  
Xinlei Chu ◽  
Hongji Dai ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Resolution ◽  
Gene Networks ◽  
Target Genes ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Contact Map ◽  
Altered Expression ◽  
Regulatory Variants ◽  
Causal Variants

Identifying causal regulatory variants and their target genes from the majority of non-coding disease-associated genetic loci is the main challenge in post-Genome-Wide Association Studies (GWAS) functional studies. Although chromosome conformation capture (3C) and its derivative technologies have been successfully applied to nominate putative causal genes for non-coding variants, many GWAS target genes have not been identified yet. This study generated a high-resolution contact map from epithelial ovarian cancer (EOC) cells with two H3K27ac-HiChIP libraries and analyzed the underlying gene networks for 15 risk loci identified from the largest EOC GWAS. By combinatory analysis of 4,021 fine-mapped credible variants of EOC GWAS and high-resolution contact map, we obtained 162 target genes that mainly enriched in cancer related pathways. Compared with GTEx eQTL genes in ovarian tissue and annotated proximal genes, 132 HiChIP targets were first identified for EOC causal variants. More than half of the credible variants (CVs) involved interactions that were over 185 kb in distance, indicating that long-range transcriptional regulation is an important mechanism for the function of GWAS variants in EOC. We also found that many HiChIP gene targets showed significantly differential expressions between normal ovarian and EOC tumor samples. We validated one of these targets by manipulating the rs9303542 located region with CRISPR-Cas9 deletion and dCas9-VP64 activation experiments and found altered expression of HOXB7 and HOXB8 at 17q21.32. This study presents a systematic analysis to identify putative target genes for causal variants of EOC, providing an in-depth investigation of the mechanisms of non-coding regulatory variants in the etiology and pathogenesis of ovarian cancer.

scholarly journals Multiple functional variants in long-range enhancer elements contribute to the risk of SNP rs965513 in thyroid cancer

2015 ◽  
Vol 112 (19) ◽  
pp. 6128-6133 ◽  
Author(s):  
Huiling He ◽  
Wei Li ◽  
Sandya Liyanarachchi ◽  
Mukund Srinivas ◽  
Yanqiang Wang ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Long Range ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Linkage Disequilibrium Block ◽  
Thyroid Tissue ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Papillary Thyroid ◽  
Functional Variants

The [A] allele of SNP rs965513 in 9q22 has been consistently shown to be highly associated with increased papillary thyroid cancer (PTC) risk with an odds ratio of ∼1.8 as determined by genome-wide association studies, yet the molecular mechanisms remain poorly understood. Previously, we noted that the expression of two genes in the region, forkhead box E1 (FOXE1) and PTC susceptibility candidate 2 (PTCSC2), is regulated by rs965513 in unaffected thyroid tissue, but the underlying mechanisms were not elucidated. Here, we fine-mapped the 9q22 region in PTC and controls and detected an ∼33-kb linkage disequilibrium block (containing the lead SNP rs965513) that significantly associates with PTC risk. Chromatin characteristics and regulatory element signatures in this block disclosed at least three regulatory elements functioning as enhancers. These enhancers harbor at least four SNPs (rs7864322, rs12352658, rs7847449, and rs10759944) that serve as functional variants. The variant genotypes are associated with differential enhancer activities and/or transcription factor binding activities. Using the chromosome conformation capture methodology, long-range looping interactions of these elements with the promoter region shared by FOXE1 and PTCSC2 in a human papillary thyroid carcinoma cell line (KTC-1) and unaffected thyroid tissue were found. Our results suggest that multiple variants coinherited with the lead SNP and located in long-range enhancers are involved in the transcriptional regulation of FOXE1 and PTCSC2 expression. These results explain the mechanism by which the risk allele of rs965513 predisposes to thyroid cancer.

scholarly journals INFERNO - INFERring the molecular mechanisms of NOncoding genetic variants

2017 ◽  
Author(s):  
Alexandre Amlie-Wolf ◽  
Mitchell Tang ◽  
Elisabeth E. Mlynarski ◽  
Pavel P. Kuksa ◽  
Otto Valladares ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Cellular Processes ◽  
Genome Wide ◽  
Causal Variants ◽  
Novel Method

AbstractThe majority of variants identified by genome-wide association studies (GWAS) reside in the noncoding genome, where they affect regulatory elements including transcriptional enhancers. We propose INFERNO (INFERring the molecular mechanisms of NOncoding genetic variants), a novel method which integrates hundreds of diverse functional genomics data sources with GWAS summary statistics to identify putatively causal noncoding variants underlying association signals. INFERNO comprehensively infers the relevant tissue contexts, target genes, and downstream biological processes affected by causal variants. We apply INFERNO to schizophrenia GWAS data, recapitulating known schizophrenia-associated genes including CACNA1C and discovering novel signals related to transmembrane cellular processes.

scholarly journals Quantifying mediation between omics layers and complex traits

2021 ◽  
Author(s):  
Marie C Sadler ◽  
Chiara Marie Paula Auwerx ◽  
Eleonora Porcu ◽  
Zoltan Kutalik
Keyword(s):  
Complex Traits ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Irritable Bowel Disease ◽  
Protein Levels ◽  
Integrative Framework ◽  
Multiple Transcripts ◽  
Irritable Bowel ◽  
In Cis

Background: High-dimensional omics datasets provide valuable resources to determine the causal role of molecular traits in mediating the path from genotype to phenotype. Making use of quantitative trait loci (QTL) and genome-wide association studies (GWASs) summary statistics, we developed a multivariable Mendelian randomization (MVMR) framework to quantify the connectivity between three omics layers (DNA methylome (DNAm), transcriptome and proteome) and their cascading causal impact on complex traits and diseases. Results: Evaluating 50 complex traits, we found that on average 37.8% (95% CI: [36.0%-39.5%]) of DNAm-to-trait effects were mediated through transcripts in the cis-region, while only 15.8% (95% CI: [11.9%-19.6%]) are mediated through proteins in cis. DNAm sites typically regulate multiple transcripts, and while found to predominantly decrease gene expression, this was only the case for 53.4% across ~47,000 significant DNAm-transcript pairs. The average mediation proportion for transcript-to-trait effects through proteins (encoded for by the assessed transcript or located in trans) was estimated to be 5.27% (95%CI: [4.11%-6.43%]). Notable differences in the transcript and protein QTL architectures were detected with only 22% of protein levels being causally driven by their corresponding transcript levels. Several regulatory mechanisms were hypothesized including an example where cg10385390 (chr1:8,022,505) increases the risk of irritable bowel disease by reducing PARK7 transcript and protein expression. Conclusions: The proposed integrative framework identified putative causal chains through omics layers providing a powerful tool to map GWAS signals. Quantification of causal effects between successive layers indicated that molecular mechanisms can be more complex than what the central dogma of biology would suggest.

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